For two weeks last July, I cocooned myself in a hotel in Portland, OR, living and breathing probabilistic programming as a “student” in the probabilistic programming summer school run by DARPA.
Stan modeling language and C++ library for Bayesian inference. NUTS adaptive HMC (MCMC) sampling, automatic differentiation, R, shell interfaces. Gelman.
This website serves as a repository of links and information about probabilistic programming languages, including both academic research spanning theory, algorithms, modeling, and systems, as well as implementations, evaluations, and applications.
H. Bai, D. Hsu, W. Lee, and V. Ngo. Algorithmic Foundations of Robotics IX, volume 68 of Springer Tracts in Advanced Robotics, chapter 11, Springer Berlin Heidelberg, Berlin, Heidelberg, (2011)